Objective. A current challenge of neurotechnologies is to develop speech brain-computer interfaces aiming at restoring communication in people unable to speak. To achieve a proof of concept of such system, neural activity of patients implanted for clinical reasons can be recorded while they speak. Using such simultaneously recorded audio and neural data, decoders can be built to predict speech features using features extracted from brain signals. A typical neural feature is the spectral power of field potentials in the high-gamma frequency band, which happens to overlap the frequency range of speech acoustic signals, especially the fundamental frequency of the voice. Here, we analyzed human electrocorticographic and intracortical recordings during speech production and perception as well as a rat microelectrocorticographic recording during sound perception. We observed that several datasets, recorded with different recording setups, contained spectrotemporal features hig...

中文翻译：

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语音产生和声音感知过程中电生理脑信号的声学污染的观察和评估

客观的。神经技术当前面临的一个挑战是开发语音脑机接口，旨在恢复无法说话的人的交流。为了实现这种系统的概念验证，可以在患者说话时记录因临床原因植入的患者的神经活动。使用这种同时记录的音频和神经数据，可以构建解码器以使用从大脑信号中提取的特征来预测语音特征。一个典型的神经特征是高伽马频带中场势的谱功率，它恰好与语音声学信号的频率范围重叠，尤其是语音的基频。这里，我们分析了语音产生和感知过程中的人类皮层电图和皮层内记录，以及声音感知过程中的大鼠微皮层电图记录。我们观察到几个数据集，用不同的记录设置记录，包含高光谱时间特征......